From f0564c233e707163993f641079f97eb13b59fc75 Mon Sep 17 00:00:00 2001 From: nojhan Date: Mon, 9 Jul 2012 22:37:40 +0200 Subject: [PATCH] test support for Eigen implementations --- edo/test/t-edoEstimatorNormalMulti.cpp | 149 +++++----------- edo/test/t-mean-distance.cpp | 224 +++++++++++++------------ 2 files changed, 158 insertions(+), 215 deletions(-) diff --git a/edo/test/t-edoEstimatorNormalMulti.cpp b/edo/test/t-edoEstimatorNormalMulti.cpp index 91d93296..c62f6dfa 100644 --- a/edo/test/t-edoEstimatorNormalMulti.cpp +++ b/edo/test/t-edoEstimatorNormalMulti.cpp @@ -40,22 +40,29 @@ typedef eoReal< eoMinimizingFitness > EOT; typedef edoNormalMulti< EOT > Distrib; typedef EOT::AtomType AtomType; +#ifdef WITH_BOOST +#include +#include + typedef ublas::vector< AtomType > Vector; + typedef ublas::symmetric_matrix< AtomType, ublas::lower > Matrix; +#else +#ifdef WITH_EIGEN +#include + typedef Eigen::Matrix< AtomType, Eigen::Dynamic, 1> Vector; + typedef Eigen::Matrix< AtomType, Eigen::Dynamic, Eigen::Dynamic> Matrix; +#endif +#endif + int main(int ac, char** av) { - //----------------------------------------------------- // (0) parser + eo routines - //----------------------------------------------------- - eoParser parser(ac, av); - std::string section("Algorithm parameters"); - - unsigned int p_size = parser.createParam((unsigned int)100, "popSize", "Population Size", 'P', section).value(); // P - - unsigned int s_size = parser.createParam((unsigned int)2, "dimension-size", "Dimension size", 'd', section).value(); // d - - AtomType mean_value = parser.createParam((AtomType)0, "mean", "Mean value", 'm', section).value(); // m + std::string section("Algorithm parameters"); + unsigned int p_size = parser.createParam((unsigned int)100, "popSize", "Population Size", 'P', section).value(); // P + unsigned int s_size = parser.createParam((unsigned int)2, "dimension-size", "Dimension size", 'd', section).value(); // d + AtomType mean_value = parser.createParam((AtomType)0, "mean", "Mean value", 'm', section).value(); // m AtomType covar1_value = parser.createParam((AtomType)1.0, "covar1", "Covar value 1", '1', section).value(); AtomType covar2_value = parser.createParam((AtomType)0.5, "covar2", "Covar value 2", '2', section).value(); AtomType covar3_value = parser.createParam((AtomType)1.0, "covar3", "Covar value 3", '3', section).value(); @@ -66,29 +73,20 @@ int main(int ac, char** av) << covar3_value << "_gen"; std::string gen_filename = ss.str(); - if (parser.userNeedsHelp()) - { - parser.printHelp(std::cout); - exit(1); - } + if( parser.userNeedsHelp() ) { + parser.printHelp(std::cout); + exit(1); + } make_verbose(parser); make_help(parser); - assert(p_size > 0); assert(s_size > 0); - eoState state; - //----------------------------------------------------- - - - //----------------------------------------------------- // (1) Population init and sampler - //----------------------------------------------------- - eoRndGenerator< double >* gen = new eoUniformGenerator< double >(-5, 5); state.storeFunctor(gen); @@ -99,18 +97,14 @@ int main(int ac, char** av) // fill population thanks to eoInit instance eoPop< EOT >& pop = state.takeOwnership( eoPop< EOT >( p_size, *init ) ); - //----------------------------------------------------- - - - //----------------------------------------------------------------------------- // (2) distribution initial parameters - //----------------------------------------------------------------------------- + Vector mean( s_size ); - ublas::vector< AtomType > mean( s_size ); + for (unsigned int i = 0; i < s_size; ++i) { + mean( i ) = mean_value; + } - for (unsigned int i = 0; i < s_size; ++i) { mean( i ) = mean_value; } - - ublas::symmetric_matrix< AtomType, ublas::lower > varcovar( s_size, s_size ); + Matrix varcovar( s_size, s_size ); varcovar( 0, 0 ) = covar1_value; varcovar( 0, 1 ) = covar2_value; @@ -118,13 +112,7 @@ int main(int ac, char** av) Distrib distrib( mean, varcovar ); - //----------------------------------------------------------------------------- - - - //----------------------------------------------------------------------------- // (3a) distribution output preparation - //----------------------------------------------------------------------------- - edoDummyContinue< Distrib >* distrib_dummy_continue = new edoDummyContinue< Distrib >(); state.storeFunctor(distrib_dummy_continue); @@ -141,60 +129,29 @@ int main(int ac, char** av) distrib_file_snapshot->add(*distrib_stat); distrib_continue->add(*distrib_file_snapshot); - //----------------------------------------------------------------------------- - - - //----------------------------------------------------------------------------- // (3b) distribution output - //----------------------------------------------------------------------------- - (*distrib_continue)( distrib ); - //----------------------------------------------------------------------------- - - - //----------------------------------------------------------------------------- // Prepare bounder class to set bounds of sampling. // This is used by edoSampler. - //----------------------------------------------------------------------------- - - edoBounder< EOT >* bounder = new edoBounderRng< EOT >(EOT(pop[0].size(), -5), - EOT(pop[0].size(), 5), - *gen); + edoBounder< EOT >* bounder = new edoBounderRng< EOT >( + EOT(pop[0].size(), -5), EOT(pop[0].size(), 5), *gen + ); state.storeFunctor(bounder); - //----------------------------------------------------------------------------- - - - //----------------------------------------------------------------------------- // Prepare sampler class with a specific distribution - //----------------------------------------------------------------------------- - edoSampler< Distrib >* sampler = new edoSamplerNormalMulti< EOT >( *bounder ); state.storeFunctor(sampler); - //----------------------------------------------------------------------------- - - - //----------------------------------------------------------------------------- // (4) sampling phase - //----------------------------------------------------------------------------- - pop.clear(); - for (unsigned int i = 0; i < p_size; ++i) - { - EOT candidate_solution = (*sampler)( distrib ); - pop.push_back( candidate_solution ); - } + for( unsigned int i = 0; i < p_size; ++i ) { + EOT candidate_solution = (*sampler)( distrib ); + pop.push_back( candidate_solution ); + } - //----------------------------------------------------------------------------- - - - //----------------------------------------------------------------------------- // (5) population output - //----------------------------------------------------------------------------- - eoContinue< EOT >* pop_cont = new eoGenContinue< EOT >( 2 ); // never reached fitness state.storeFunctor(pop_cont); @@ -212,53 +169,31 @@ int main(int ac, char** av) (*pop_continue)( pop ); - //----------------------------------------------------------------------------- - - - //----------------------------------------------------------------------------- // (6) estimation phase - //----------------------------------------------------------------------------- - edoEstimator< Distrib >* estimator = new edoEstimatorNormalMulti< EOT >(); state.storeFunctor(estimator); distrib = (*estimator)( pop ); - //----------------------------------------------------------------------------- - - - //----------------------------------------------------------------------------- // (7) distribution output - //----------------------------------------------------------------------------- - (*distrib_continue)( distrib ); - //----------------------------------------------------------------------------- - - - //----------------------------------------------------------------------------- // (8) euclidianne distance estimation - //----------------------------------------------------------------------------- - - ublas::vector< AtomType > new_mean = distrib.mean(); - ublas::symmetric_matrix< AtomType, ublas::lower > new_varcovar = distrib.varcovar(); + Vector new_mean = distrib.mean(); + Matrix new_varcovar = distrib.varcovar(); AtomType distance = 0; - - for ( unsigned int d = 0; d < s_size; ++d ) - { - distance += pow( mean[ d ] - new_mean[ d ], 2 ); - } + for( unsigned int d = 0; d < s_size; ++d ) { + distance += pow( mean[ d ] - new_mean[ d ], 2 ); + } distance = sqrt( distance ); eo::log << eo::logging - << "mean: " << mean << std::endl - << "new mean: " << new_mean << std::endl - << "distance: " << distance << std::endl - ; - - //----------------------------------------------------------------------------- + << "mean: " << mean << std::endl + << "new mean: " << new_mean << std::endl + << "distance: " << distance << std::endl + ; return 0; } diff --git a/edo/test/t-mean-distance.cpp b/edo/test/t-mean-distance.cpp index 8e62c378..d119c1a9 100644 --- a/edo/test/t-mean-distance.cpp +++ b/edo/test/t-mean-distance.cpp @@ -37,8 +37,6 @@ Authors: #include -#include -#include #include "Rosenbrock.h" #include "Sphere.h" @@ -47,15 +45,25 @@ typedef eoReal< eoMinimizingFitness > EOT; typedef edoNormalMulti< EOT > Distrib; typedef EOT::AtomType AtomType; +#ifdef WITH_BOOST +#include +#include + typedef ublas::vector< AtomType > Vector; + typedef ublas::symmetric_matrix< AtomType, ublas::lower > Matrix; +#else +#ifdef WITH_EIGEN +#include + typedef Eigen::Matrix< AtomType, Eigen::Dynamic, 1> Vector; + typedef Eigen::Matrix< AtomType, Eigen::Dynamic, Eigen::Dynamic> Matrix; +#endif +#endif + int main(int ac, char** av) { - //----------------------------------------------------- // (0) parser + eo routines - //----------------------------------------------------- - eoParser parser(ac, av); - std::string section("Algorithm parameters"); + std::string section("Algorithm parameters"); unsigned int r_max = parser.createParam((unsigned int)100, "run-number", "Number of run", 'r', section).value(); // r unsigned int p_min = parser.createParam((unsigned int)10, "population-min", "Population min", 'p', section).value(); // p @@ -72,15 +80,15 @@ int main(int ac, char** av) std::string files_description = parser.createParam((std::string)"files_description.txt", "files-description", "Files description", 'F', section).value(); // F if (parser.userNeedsHelp()) - { - parser.printHelp(std::cout); - exit(1); - } + { + parser.printHelp(std::cout); + exit(1); + } make_verbose(parser); make_help(parser); - //----------------------------------------------------- + assert(r_max >= 1); assert(s_size >= 2); @@ -90,139 +98,139 @@ int main(int ac, char** av) ::mkdir( results_directory.c_str(), 0755 ); for ( unsigned int p_size = p_min; p_size <= p_max; p_size += p_step ) - { - assert(p_size >= p_min); + { + assert(p_size >= p_min); - std::ostringstream desc_file; - desc_file << results_directory << "/" << files_description; + std::ostringstream desc_file; + desc_file << results_directory << "/" << files_description; - std::ostringstream cur_file; - cur_file << results_directory << "/pop_" << p_size << ".txt"; + std::ostringstream cur_file; + cur_file << results_directory << "/pop_" << p_size << ".txt"; - eo::log << eo::file( desc_file.str() ) << cur_file.str().c_str() << std::endl; + eo::log << eo::file( desc_file.str() ) << cur_file.str().c_str() << std::endl; - eo::log << eo::file( cur_file.str() ); + eo::log << eo::file( cur_file.str() ); - eo::log << eo::logging << "run_number p_size s_size mean(0) mean(1) new-mean(0) new-mean(1) distance" << std::endl; + eo::log << eo::logging << "run_number p_size s_size mean(0) mean(1) new-mean(0) new-mean(1) distance" << std::endl; - eo::log << eo::quiet; + eo::log << eo::quiet; - for ( unsigned int r = 1; r <= r_max; ++r) - { + for ( unsigned int r = 1; r <= r_max; ++r) + { - eoState state; + eoState state; - //----------------------------------------------------- - // (1) Population init and sampler - //----------------------------------------------------- - eoRndGenerator< double >* gen = new eoUniformGenerator< double >(-5, 5); - state.storeFunctor(gen); - - eoInitFixedLength< EOT >* init = new eoInitFixedLength< EOT >( s_size, *gen ); - state.storeFunctor(init); - - // create an empty pop and let the state handle the memory - // fill population thanks to eoInit instance - eoPop< EOT >& pop = state.takeOwnership( eoPop< EOT >( p_size, *init ) ); - - //----------------------------------------------------- + // (1) Population init and sampler - //----------------------------------------------------------------------------- - // (2) distribution initial parameters - //----------------------------------------------------------------------------- + eoRndGenerator< double >* gen = new eoUniformGenerator< double >(-5, 5); + state.storeFunctor(gen); - ublas::vector< AtomType > mean( s_size, mean_value ); - ublas::symmetric_matrix< AtomType, ublas::lower > varcovar( s_size, s_size ); + eoInitFixedLength< EOT >* init = new eoInitFixedLength< EOT >( s_size, *gen ); + state.storeFunctor(init); - varcovar( 0, 0 ) = covar1_value; - varcovar( 0, 1 ) = covar2_value; - varcovar( 1, 1 ) = covar3_value; - - Distrib distrib( mean, varcovar ); - - //----------------------------------------------------------------------------- + // create an empty pop and let the state handle the memory + // fill population thanks to eoInit instance + eoPop< EOT >& pop = state.takeOwnership( eoPop< EOT >( p_size, *init ) ); - //----------------------------------------------------------------------------- - // Prepare bounder class to set bounds of sampling. - // This is used by edoSampler. - //----------------------------------------------------------------------------- - - edoBounder< EOT >* bounder = new edoBounderRng< EOT >(EOT(pop[0].size(), -5), - EOT(pop[0].size(), 5), - *gen); - state.storeFunctor(bounder); - - //----------------------------------------------------------------------------- - //----------------------------------------------------------------------------- - // Prepare sampler class with a specific distribution - //----------------------------------------------------------------------------- - edoSampler< Distrib >* sampler = new edoSamplerNormalMulti< EOT >( *bounder ); - state.storeFunctor(sampler); - - //----------------------------------------------------------------------------- + // (2) distribution initial parameters - //----------------------------------------------------------------------------- - // (4) sampling phase - //----------------------------------------------------------------------------- + Vector mean( s_size, mean_value ); + Matrix varcovar( s_size, s_size ); - pop.clear(); + varcovar( 0, 0 ) = covar1_value; + varcovar( 0, 1 ) = covar2_value; + varcovar( 1, 1 ) = covar3_value; - for (unsigned int i = 0; i < p_size; ++i) - { - EOT candidate_solution = (*sampler)( distrib ); - pop.push_back( candidate_solution ); - } - - //----------------------------------------------------------------------------- + Distrib distrib( mean, varcovar ); - //----------------------------------------------------------------------------- - // (6) estimation phase - //----------------------------------------------------------------------------- - - edoEstimator< Distrib >* estimator = new edoEstimatorNormalMulti< EOT >(); - state.storeFunctor(estimator); - - distrib = (*estimator)( pop ); - - //----------------------------------------------------------------------------- - //----------------------------------------------------------------------------- - // (8) euclidianne distance estimation - //----------------------------------------------------------------------------- - ublas::vector< AtomType > new_mean = distrib.mean(); - ublas::symmetric_matrix< AtomType, ublas::lower > new_varcovar = distrib.varcovar(); + // Prepare bounder class to set bounds of sampling. + // This is used by edoSampler. - AtomType distance = 0; - for ( unsigned int d = 0; d < s_size; ++d ) - { - distance += pow( mean[ d ] - new_mean[ d ], 2 ); - } + edoBounder< EOT >* bounder = new edoBounderRng< EOT >(EOT(pop[0].size(), -5), + EOT(pop[0].size(), 5), + *gen); + state.storeFunctor(bounder); - distance = sqrt( distance ); - eo::log << r << " " << p_size << " " << s_size << " " - << mean(0) << " " << mean(1) << " " - << new_mean(0) << " " << new_mean(1) << " " - << distance << std::endl - ; - //----------------------------------------------------------------------------- - } - } + // Prepare sampler class with a specific distribution + + + edoSampler< Distrib >* sampler = new edoSamplerNormalMulti< EOT >( *bounder ); + state.storeFunctor(sampler); + + + + + + // (4) sampling phase + + + pop.clear(); + + for (unsigned int i = 0; i < p_size; ++i) + { + EOT candidate_solution = (*sampler)( distrib ); + pop.push_back( candidate_solution ); + } + + + + + + // (6) estimation phase + + + edoEstimator< Distrib >* estimator = new edoEstimatorNormalMulti< EOT >(); + state.storeFunctor(estimator); + + distrib = (*estimator)( pop ); + + + + + + // (8) euclidianne distance estimation + + + Vector new_mean = distrib.mean(); + Matrix new_varcovar = distrib.varcovar(); + + AtomType distance = 0; + + for ( unsigned int d = 0; d < s_size; ++d ) + { + distance += pow( mean[ d ] - new_mean[ d ], 2 ); + } + + distance = sqrt( distance ); + + eo::log << r << " " << p_size << " " << s_size << " " + << mean(0) << " " << mean(1) << " " + << new_mean(0) << " " << new_mean(1) << " " + << distance << std::endl + ; + + + + } + + } return 0; }